Abstract
Mobile Edge Cloud (MEC) technology is envisioned to play a key role in next generation mobile networks by supporting low-latency applications using geographically distributed local cloud clusters. However, MEC faces challenges of resource assignment and load balancing to support user mobility and latency-sensitive applications. Virtualized resource reallocation techniques including dynamic service migration are evolving to achieve load balance, fault tolerance and system maintenance objectives for resource constrained edge nodes. In this work, a compute and network-aware lightweight resource sharing framework with dynamic container migration, ShareOn, is proposed. The migration framework is validated using a set of heterogeneous edge cloud nodes distributed in San Francisco city, serving mobile taxicab users across that region. The end-to-end system is implemented using a container hypervisor called LXD (Linux Container Hypervisor) executing a real-time application to detect license number plates in automobiles. The system is evaluated based on key metrics associated with application quality-of-service (QoS) and network efficiency such as the average system response time and the migration cost for different combinations of load, compute resources, inter-edge cloud bandwidth, network and user latency. A detailed migration cost analysis enables evaluation of migration strategies to improve ShareOn’s performance in comparison to alternative migration techniques, achieving a gain of 15–22% in system response time for highly loaded edge cloud nodes.
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